Acta Geographica Sinica ›› 2021, Vol. 76 ›› Issue (4): 903-920.doi: 10.11821/dlxb202104009

• Agricultural and Rural Development • Previous Articles     Next Articles

The geographical pattern and differentiational mechanism of rural poverty in China

ZHOU Yang1,2,3(), LI Xunhuan1,2,3, TONG Chunyang1,2,3, HUANG Han1,2,3   

  1. 1. Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    2. Center for Assessment and Research on Targeted Poverty Alleviation, CAS, Beijing 100101, China
    3. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2020-01-05 Revised:2020-10-19 Online:2021-04-25 Published:2021-06-25
  • Supported by:
    National Natural Science Foundation of China(41871183);National Natural Science Foundation of China(41601172);Strategic Priority Research Program of the Chinese Academy of Sciences(XDA23070301);China Postdoctoral Science Foundation(2016M591105)

Abstract:

Poverty eradication is a worldwide concern. Regional impoverishment has been considered to be closely related to the geographical environment. Therefore, the relationship between poverty and geographical environment has become the core content of poverty geography. Based on the theoretical basis of regional multidimensional poverty and impoverished areal system, this study constructed a "poverty-environment-economy-society" analytical framework to examine the nexus between poverty and geo-environment. On this basis, taking 124000 poverty-stricken villages as the research object, this study used the methods of spatial autocorrelation, kernel density analysis and geographical detector to depict the spatial geographical pattern of China's poverty-stricken villages in the new era, quantitatively detect the leading factors of the regional differentiation of poverty-stricken villages, and reveal the interaction mechanism between the village impoverishment and the geographical environment. The main conclusions can be drawn in the following three aspects. First of all, poverty and the geo-environment interact with each other, and the paths and manifestations of the interaction between the two are complex and diverse. In general, factors leading to village poverty can be detected from the two categories of nature and humanities and the three dimensions of environment, economy, and society. Environmental factors play a fundamental role in the evolution of poverty, economic factors are the most direct and important contributor to impoverishment, and social factors have a magnifying effect on poverty. Secondly, the distribution of poor villages in China has obvious spatial agglomeration characteristics. The spatial distribution pattern of poverty-stricken villages across the country is consistent with the basic geographic pattern depicted by the Hu Huanyong Line and the three-level topography, with obvious vertical and slope differentiation characteristics. The poor villages in China are spatially distributed with one first-level core area, five second-level core areas and seven third-level core areas. Last but not least, the spatial distribution pattern of poor villages in China is the result of the interaction of multiple factors. Topography, natural resources endowment, labors, transportation and public services were identified as the main contributors to spatial differentiation of poor villages in China. Interaction detection results indicated that the driving force between two-factor interaction is stronger than that of a single factor, and the interaction types are non-linear enhancement except for topographic factors and location. Facing the 2030 UN Sustainable Development Goals, China needs to establish the long-term mechanism to effectively link up poverty reduction, rural revitalization, ecological civilization construction, territorial space optimization and urban-rural integrated development, so as to stimulate the endogenous development momentum of poverty-stricken areas and promote regional sustainable development.

Key words: poverty-stricken village, spatial heterogeneity, geographic factor, geodetector, poverty geography, rural revitalization